POS0969 GENETIC AND MOLECULAR DISTINCTIONS BETWEEN AXIAL PSORIATIC ARTHRITIS AND ANKYLOSING SPONDYLITIS
Authors: A. Kavanaugh, X. Baraliakos, S. Gao, W. Chen, K. Sweet, S. D. Chakravarty, Q. Song, M. Shawi, F. Behrens, P. Rahman
Journal: Annals of the Rheumatic Diseases (2022)

Background Psoriatic arthritis (PsA) and ankylosing spondylitis (AS) represent the prototypical spondyloarthritides. PsA patients may also suffer from axial disease (axPsA). Despite overlapping symptoms, axPsA and AS may be distinct disorders with differing clinical manifestations, genetic associations, and radiographic findings. 1 These disorders also respond differently to immunomodulatory therapies such as anti-interleukin (IL)-23 inhibitors. While guselkumab, a human monoclonal antibody targeting the IL-23p19 subunit, improved symptoms of axPsA, 2 risankizumab, a humanized monoclonal antibody targeting the IL-23p19 subunit, did not show improvement in the primary endpoint of proportion of AS patients achieving an Assessment of SpondyloArthritis International Society 40% (ASAS40) response at week (W) 12. 3 Objectives To understand molecular distinctions between axPsA and AS to differentiate these diseases and guide treatment choice. Methods Whole blood and serum samples were collected from consenting patients in the NCT03162796 /NCT0315828 studies of guselkumab in PsA and the NCT02437162 /NCT02438787 studies of ustekinumab in AS. axPsA patients were investigator-verified as having magnetic resonance imaging- or pelvic x-ray-confirmed sacroiliitis at screening (locally read). Human leukocyte antigen (HLA) genotypes were determined by RNA sequencing, limited to Caucasian patients to reduce genetic variability, 4 and select serum cytokine levels were analyzed alongside samples from healthy individuals. Differential prevalence of HLA alleles in axPsA versus AS was determined using a Fisher’s Exact test. Statistical significance of differential baseline serum cytokine expression among axPsA versus non-axPsA versus AS patients, and of guselkumab effect on serum cytokine reduction versus placebo among axPsA and non-axPsA patients, were determined with a generalized linear model performed on log2-transformed data. Biomarker data from guselkumab every-4-weeks and every-8-weeks treatment arms were pooled. Results Among the 186/234 Caucasian axPsA/AS patients with available data, 34%/15% were female, 70%/14% used methotrexate at baseline, mean serum C-reactive protein (CRP) levels were 2.8/2.4 mg/dL and mean Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) scores were 6.4/7.5, respectively. Aside from race, baseline demographics and disease characteristics were representative of the overall population. The prevalence of class I HLA allele -B27, -C01, and -C02 carriers was significantly lower in axPsA than AS patients (30.7% versus 92.3%, p&lt;0.001; 5.9% versus 31.6%, p&lt;0.001; and 28.0% versus 62.0%, p&lt;0.001, respectively), while the prevalence of HLA-C06 was significantly higher in axPsA than AS populations (36.0% versus 8.6%, p&lt;0.001). Baseline serum levels of IL-17A and IL-17F were significantly higher in axPsA (N=71) than in AS (N=58) patients (p&lt;0.01 and p&lt;0.001, respectively). Comparable IL-17A/F expression was seen for axPsA and non-axPsA (N=229) patients (both p=not significant). Significant and comparable reductions from baseline in serum IL-17A/F in axPsA and non-axPsA patients were seen with guselkumab treatment (axPsA N=41, non-axPsA N=160) versus placebo (axPsA N=30, non-axPsA N=69) at W4/24 (all p&lt;0.05). Conclusion Adults with axPsA and AS exhibit different genetic risk factors and serum IL-17 levels, supporting the concept of distinct disorders. Guselkumab demonstrated significant pharmacodynamic effects in axPsA patients that aligned with such effects in non-axPsA patients, consistent with observed clinical improvement. 2 References [1]Feld et al. Nat Rev Rheumatol. 2018;14(6):363-371. [2]Mease et al. Lancet Rheumatol. 2021;3(10)E715-E723. [3]Baeten et al. Ann Rheum Dis . 2018;77(9):1295-1302. [4]Buchkovich et al. Genome Med. 2017;9(86). Disclosure of Interests Arthur Kavanaugh Consultant of: AbbVie, Amgen, BMS, Genentech, Janssen, Eli Lilly, Merck, Novartis, Pfizer and UCB, Xenofon Baraliakos Consultant of: AbbVie, Chugai, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: AbbVie, MSD, and Novartis, Sheng Gao Employee of: Janssen Research &amp; Development, LLC, and may own stock or stock options in Johnson &amp; Johnson, Warner Chen Employee of: Janssen Research &amp; Development, LLC, and may own stock or stock options in Johnson &amp; Johnson, Kristen Sweet Employee of: Janssen Research &amp; Development, LLC, and may own stock or stock options in Johnson &amp; Johnson, Soumya D Chakravarty Employee of: Janssen Scientific Affairs, LLC, and may own stock or stock options in Johnson &amp; Johnson, Qingxuan Song Employee of: Janssen Research &amp; Development, LLC, and may own stock or stock options in Johnson &amp; Johnson, May Shawi Employee of: Janssen Pharmaceutical Companies of Johnson &amp; Johnson, and may own stock or stock options in Johnson &amp; Johnson, Frank Behrens Speakers bureau: AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Chugai, Eli Lilly, Galapagos, Genzyme, Gilead, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Chugai, Eli Lilly, Galapagos, Genzyme, Gilead, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Grant/research support from: Celgene, Chugai, Janssen, Pfizer, and Roche, Proton Rahman Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support from: Janssen, research grants from Janssen and Novartis